Author

Tassiani Sarretto

University of Wollongong

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:batch correction / integration· 1 Approach:deep learning· 1 Assay:multiome· 1

Frequent Co-Authors

Alejandro SifrimiD· 1 shared Anis IsmailiD· 1 shared David WoutersiD· 1 shared Fabio SocciarelliiD· 1 shared Gabriele ParteliD· 1 shared Jakub IdkowiakiD· 1 shared Jelle JacobsiD· 1 shared Johannes V. SwinneniD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Alejandro SifrimORCID

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1 paper

Recent·Most cited

Multi-omics integration and batch correction using a modality-agnostic deep learning framework

Jose Ignacio Alvira Larizgoitia, Gabriele Partel, Lorenzo Venturelli, Wanqiu Zhang, Xander Spotbeen, Sebastiaan Vanuytven, Sam Kint, Katy Vandereyken, David Wouters, Anis Ismail, Regis Scarceriaux, Jakub Idkowiak, Tassiani Sarretto, Shane R. Ellis, Massimo F. Loda, , Alejandro Sifrim

This paper introduces MIMA, a deep learning framework for multi-omics integration and batch correction, which effectively removes batch effects and preserves biological information across modalities.

bioRxiv · Oct 21, 2025 · PreprintBioinformatics